An Open-source Python framework for constraint programming and optimization

The Qaekwy Python Client serves as a powerful tool to interact with the Qaekwy optimization solver engine through its API. This client provides a convenient and programmatic way to create, model, and solve optimization problems by streamlining the process of formulating complex problems and finding optimal solutions.

Qaekwy is small optimization problem solver engine designed to provide powerful modeling capabilities and efficient solving algorithms to find optimal solutions to complex problems.

• Variables: Supports integer, float, and boolean variables, including arrays for complex models.
• Constraints: Offers a wide range of constraints for flexible problem modeling.
• Optimization: Minimize or maximize objective functions to find optimal solutions.
• Flexible Search Strategies: Choose from algorithms like Depth-First Search (DFS) and Branch and Bound (BAB).

Explore the Qaekwy Documentation for in-depth guides, examples, and usage details.

• Python 3.12 or higher
• pip (Python package manager)

pip install qaekwy 

python -m qaekwy --version 

Get started with Qaekwy in just a few steps:

• Create a model by defining:
  • variables
  • constraints
  • objectives (optional)
• Run your model and retrieve solutions.

See the Example below for a practical demonstration:

from qaekwy.engine import DirectEngine from qaekwy.model.specific import SpecificMaximum from qaekwy.model.variable.integer import ( IntegerVariable, IntegerExpressionVariable ) from qaekwy.model.modeller import Modeller from qaekwy.model.searcher import SearcherType # Define the optimization model class SimpleOptimizationProblem(Modeller): def __init__(self): super().__init__() # Define integer variables with domain [0, 10] x = IntegerVariable("x", domain_low=0, domain_high=10) y = IntegerVariable("y", domain_low=0, domain_high=10) z = IntegerExpressionVariable("z", expression=y - x) # Add variables to the model self.add_variable(x).add_variable(y).add_variable(z) # Define constraints self.add_constraint(y > 2 * x) self.add_constraint(x >= 4) # Set objective: Maximize z self.add_objective( SpecificMaximum(variable=z) ) # Set search strategy self.set_searcher(SearcherType.BAB) # Instantiate the cloud-based solver qaekwy_engine = DirectEngine() # Build and solve the model model = SimpleOptimizationProblem() response = qaekwy_engine.model(model=model) # Display solutions for solution in response.get_solutions(): print(f"Optimal solution:") print(f"- x = {solution.x}") print(f"- y = {solution.y}") print(f"- z = {solution.z}")

Output:

Optimal solution: - x = 4 - y = 10 - z = 6 

• Released under the European Union Public Licence 1.2 (EUPL 1.2).
• Qaekwy backend Terms & Conditions